A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments

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A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments

一種在無GPS環境中設計的面向低價微型飛行器的多感應器同步定位成圖系統

學術編輯：Gonzalo Pajares Martinsanz
收到：2017年1月25日；接受：2017年4月5日；發布時間：4月8日201

Abstract: One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory con?guration of the aerial robot, by integrating different state-of-the art SLAM methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF). To do this, a minimum onboard sensory con?guration is supposed, consisting of a monocular camera, an Inertial Measurement Unit (IMU) and an altimeter. It allows to improve the results of well-known monocular visual SLAM methods (LSD-SLAM and ORB-SLAM are tested and compared in this work) by solving scale ambiguity and providing additional information to the EKF.When payload and computational capabilities permit, a 2D laser sensor can be easily incorporated to the SLAM system, obtaining a local 2.5D map and a footprint estimation of the robot position that improves the 6D pose estimation through the EKF. We present some experimental results with two different commercial platforms, and validate the system by applying it to their position control.

簡介：空中機器人在無GPS訊號的環境中的一個主要挑戰是只使用可用的機載感應器的位置估計。本文提出了一種同時建圖和定位（SLAM）系統，它可以遠程計算不同低價格商用航空平台的位姿和環境地圖，遠程計算的原因是機載計算能力通常是受限的。該系統適合於空中機器人的感應器配置，通過融合不同的先進的SLAM方法，包括視覺SLAM，雷射雷達SLAM和/或者使用EKF的慣性測量。要做到這一點，一種最小的機載感測配置是可以做到的，包括一個單目相機、一個慣性測量單位（IMU）和一個高度計。

A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments